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In this paper we give an improvement of the degree of the homogeneous linear recurrence with integer coefficients that exponential sums of symmetric Boolean functions satisfy. This improvement is tight. We also compute the asymptotic…

Number Theory · Mathematics 2011-01-26 Francis N. Castro , Luis A. Medina

Motion polynomials (polynomials over the dual quaternions with nonzero real norm) describe rational motions. We present a necessary and sufficient condition for reduced bounded motion polynomials to admit factorizations into monic linear…

Rings and Algebras · Mathematics 2024-12-03 Zijia Li , Hans-Peter Schröcker , Mikhail Skopenkov , Daniel F. Scharler

We study qualitative properties of the set of recurrent points of finitely generated free semigroups of measurable maps. In the case of a single generator the classical Poincare recurrence theorem shows that these properties are closely…

Dynamical Systems · Mathematics 2020-08-13 Michael Blank

Let $(G_n(x))_{n=0}^\infty$ be a $d$-th order linear recurrence sequence having polynomial characteristic roots, one of which has degree strictly greater than the others. Moreover, let $m\geq 2$ be a given integer. We ask for…

Number Theory · Mathematics 2018-10-30 Clemens Fuchs , Christina Karolus

Often, polynomials or rational functions, orthogonal for a particular inner product are desired. In practical numerical algorithms these polynomials are not constructed, but instead the associated recurrence relations are computed.…

Numerical Analysis · Mathematics 2023-11-28 Marc Van Barel , Niel Van Buggenhout , Raf Vandebril

We propose a general method for optimization with semi-infinite constraints that involve a linear combination of functions, focusing on the case of the exponential function. Each function is lower and upper bounded on sub-intervals by…

Optimization and Control · Mathematics 2014-01-13 Bogdan Dumitrescu , Bogdan C. Sicleru , Florin Avram

Power series in which the summand satisfies a linear recurrence relation with polynomial coefficients are shown to be the solution of a linear differential or algebraic equation. Solving the associated differential or algebraic equation…

General Mathematics · Mathematics 2026-01-19 Erik Talvila

We construct fast, structure-preserving iterations for computing the sign decomposition of a unitary matrix $A$ with no eigenvalues equal to $\pm i$. This decomposition factorizes $A$ as the product of an involutory matrix $S =…

Numerical Analysis · Mathematics 2020-11-26 Evan S. Gawlik

Multivariate functions emerge naturally in a wide variety of data-driven models. Popular choices are expressions in the form of basis expansions or neural networks. While highly effective, the resulting functions tend to be hard to…

Machine Learning · Statistics 2022-06-15 Jan Decuyper , Koen Tiels , Siep Weiland , Mark C. Runacres , Johan Schoukens

The aim of this paper is to prove ergodic decomposition theorems for probability measures quasi-invariant under Borel actions of inductively compact groups (Theorem 1) as well as for sigma-finite invariant measures (Corollary 1). For…

Dynamical Systems · Mathematics 2014-07-28 Alexander I. Bufetov

In the paper, we give partition-theoretic results for the coefficients of some mock theta functions and prove their congruence properties. Some recurrence relations connecting the coefficients of the mock theta functions with certain…

Number Theory · Mathematics 2024-02-28 Sabi Biswas , Nipen Saikia

We consider the problem of decomposing a regular non-negative function as a sum of squares of functions which preserve some form of regularity. In the same way as decomposing non-negative polynomials as sum of squares of polynomials allows…

Optimization and Control · Mathematics 2022-03-01 Ulysse Marteau-Ferey , Francis Bach , Alessandro Rudi

A common problem in various applications is the additive decomposition of the output of a function with respect to its input variables. Functions with binary arguments can be axiomatically decomposed by the famous Shapley value. For the…

Mathematical Finance · Quantitative Finance 2023-03-15 Marcus C Christiansen

Inference in expressive probabilistic models is generally intractable, which makes them difficult to learn and limits their applicability. Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even…

Machine Learning · Computer Science 2016-11-14 Abram L. Friesen , Pedro Domingos

We develop a framework to analyse invariant decompositions of elements of tensor product spaces. Namely, we define an invariant decomposition with indices arranged on a simplicial complex, and which is explicitly invariant under a group…

Combinatorics · Mathematics 2024-03-05 Gemma De las Cuevas , Matt Hoogsteder Riera , Tim Netzer

This paper builds and extends on the authors' previous work related to the algorithmic tool, Cylindrical Algebraic Decomposition (CAD), and one of its core applications, Real Quantifier Elimination (QE). These topics are at the heart of…

Symbolic Computation · Computer Science 2025-11-20 James H. Davenport , Matthew England , Scott McCallum , Ali K. Uncu

This article is devoted to the study of the asymptotic behavior of the zero-energy deformations set of a periodic nonlinear composite material. We approach the problem using two-scale Young measures. We apply our analysis to show that…

Analysis of PDEs · Mathematics 2007-05-23 Marco Barchiesi

If a quantum experiment includes random processes, then the results of repeated measurements can appear consistent with irreversible decoherence even if the system's evolution prior to measurement was reversible and unitary. Two thought…

Quantum Physics · Physics 2012-06-01 Sam Kennerly

In this work, we establish a representation theorem for multivariable totally symmetric functions: a multisymmetric continuous function must be the composition of a continuous function and a set of generators of the multisymmetric…

Classical Analysis and ODEs · Mathematics 2024-12-25 Chongyao Chen , Ziang Chen , Jianfeng Lu

Submodular functions describe a variety of discrete problems in machine learning, signal processing, and computer vision. However, minimizing submodular functions poses a number of algorithmic challenges. Recent work introduced an…

Optimization and Control · Mathematics 2014-11-06 Robert Nishihara , Stefanie Jegelka , Michael I. Jordan